Multi-commodity image synthesis method and device, electronic equipment and storage medium

Abstract

The invention discloses a multi-commodity image synthesis method and device, electronic equipment and a storage medium. The method relates to the field of deep learning, and can comprise the steps: collecting a commodity image of a commodity for any commodity, carrying out the main body detection of the commodity image, and determining a binary segmentation image corresponding to the commodity according to a main body detection result and a constructed collection scene background image; and when a multi-commodity image needs to be synthesized, obtaining an application scene background image, synthesizing the at least two binary segmentation images to the application scene background image, and performing assignment on pixel points in the binary segmentation images according to the commodity images corresponding to the binary segmentation images and corresponding pixel point values in the application scene background image. By applying the scheme of the invention, the labor cost can besaved, and the processing efficiency can be improved.

Description

technical field [0001] This application relates to the field of computer applications, and in particular to a multi-commodity image synthesis method, device, electronic equipment, and storage medium in the field of deep learning. Background technique [0002] The retail industry is a labor-intensive industry, in which the cashier settlement occupies a relatively high cost, especially the labor cost. Especially during peak consumption hours, the lack of settlement manpower will seriously affect people's consumption experience. [0003] With the development of deep learning technology, it is the general trend to use computer vision to automatically generate settlement lists in settlement scenarios, that is, self-service settlement, so as to reduce costs and increase efficiency in the retail industry. In order to ensure the performance of self-service settlement, a large amount of training data that is the same as the real settlement scenario is required to train the deep lear...

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